Product Excellence Program helps Siemens PLM Software to understand how customers use their products and assists them in improving the software in future releases .The Product Excellence Program is designed to protect the privacy of the user and the intellectual property created through the use of Siemens PLM Software products. It’s used to collect data about Siemens PLM Active Workspace product usage and associated Teamcenter platform installation. Data collection occurs in the background as software is used and does not affect performance or functionality, collected data is sent to Siemens PLM Software for analysis. Per Siemens PLM no contact information is contained in the data collected not any information about data created or managed is collected. Data is solely for use by Siemens PLM Software and is never shared with third parties .

Participation in the Product Excellence Program is enabled by default during installation using either TEM or Deployment Center. System administrators can always opt out during install. Post install, participation can be controlled with the TC_ProductExcellenceProgram site preference. All data collection is anonymous and includes product usage; Teamcenter server platform (version, platform, architecture), client environment (browser type, version), client page visits and collected data is sent from the client browser.

Share this:

This topic has always been very popular and this problem has always been very complicated in FEA user community since the inception of Abaqus, or any non-linear FEA code in general. In this brief article, I will highlight few simulation situations where Abaqus standard may not be a good candidate from convergence perspective. Identifying these situations early during pre-processing and working in Explicit right away may save lots of time and efforts that otherwise would be wasted in trying Abaqus Standard.

Look at the motion aspect: We always say that simulation is not the complete replacement of physical testing right away. In the beginning physical tests play a critical role in identifying right approach for simulation as well as in data correlation between physical and virtual tests. Look closely at the physical test. Is there a large relative motion between different parts involved? If yes, then Standard is very likely to face convergence problems, even if problem is static by nature. Standard has an option of “small sliding” and “finite sliding”. But user should remember the difference between “finite sliding” and “large sliding”. Attached is the video of wire crimping simulation that ideally is a static problem but numerically not a good candidate for Standard, primarily because of motion.

Clock time matters: Apart from magnitude of motion, the duration of motion matters as well. While looking at physical test, closely look at the time in which motion is completed. If too much of motion is covered in too less time, problem is indeed dynamic instead of static as inertia effects cannot be ignored. In such a situation either Standard dynamics or Explicit would be the right way to go. Which one to choose really depends on event duration. If a lot of dynamic phenomenon happens in the order of milliseconds or microseconds, Explicit is only option for this candidate.

Is there a severe discontinuous contact: In the status file of Abaqus Standard, there is an undesirable column called SDI’s. It’s called severe discontinuous iterations and too many of these often always leads to convergence nightmare. The reason of SDI’s is discontinuous contact, also known as “chattering”. It’s a phenomenon in which nodes between two bodies in contact continuously change their contact status from OPEN to CLOSE from one iteration to the other as analysis proceeds. If chattering occurs due to modeling errors, it can be corrected but at times discontinuous contact is the nature of problem itself. In such a situation, explicit is the only approach to be taken, even for long duration events with respect to physical time. The attached video is an example of a dynamic event that would only solve in explicit or multi body dynamics, primarily because of severe discontinuous contact.

Is there too much Plasticity: Abaqus has material models to capture plasticity but there is a limit on the magnitude of Plasticity Abaqus Standard can handle. If the permanent deformation becomes so high that underlying part completely loses its load carrying capacity then Newton Raphson method of Abaqus Standard would not be able to establish equilibrium and further leading to non-convergence. Ideally, there is no further need to perform simulation as it’s a classic situation of part failure but if further simulation is needed, it should be continued in Explicit using Restart options.

Share this:

My last blog focused on the need for a Manufacturing BOM (mBOM). When organizations start to embrace the value of mBOM and decide to invest on solutions to manage a mBOM, the first question is where to master it , PLM or ERP ?

The answer to that question varies depending on the maturity level of PLM and ERP adoption and penetration in the organization . If both PLM & ERP are at the same or similar maturity level, then there are many good reasons to author & manage mBOM in a PLM system and to make ERP a consumer of the mBOM mastered in PLM.

First, in PLM mBOM is integrated with the eBOM and design process . eBOM integration and reuse enables front loading, and helps manufacturing team to lower cost of mBOM authoring and management and shorten time to market. Manufacturing users can also leverage the 3D visualization data in mBOM for better decisions and better quality. With the master model approach being adopted by leading organizations, there is lot of Product Manufacturing Information (PMI) on the 3D Master Model, which can be leveraged in both mBOM and downstream process planning. mBOM can also act as the starting point for detailed process planning to create the Bill of Process (BOP) inside PLM . BOP or Routing can also leverage the 3D visualization data to produce visual work instructions , which will always remain updated with the upstream design changes. The process plans can also be simulated and validated (feasibility, human ergo, collision etc) before actual execution. The validated Routing then get sent to Manufacturing Execution Systems (MES) along with the visual work instructions. That way there is full traceabilty from CAD to eBOM to mBOM to BOP and eventually to MES.

The traceability enables users to run where used queries among all products and plants during a change process. This ensures all product changes are evaluated for impacts in both engineering and manufacturing contexts.

Share this:

Embracing a true PLM platform and solution is not an easy endeavor for many companies, even with the reckoning of the potential value and ROI offered by a rightly architected PLM solution. Success in any Enterprise software implementation like PLM often requires careful planning, dedicated resources , right technical expertise, executive sponsorship, and a receptive culture, among other things. When done the right way the results of such efforts are transformational, producing significant business benefit which can be measured and validated.

One of the biggest challenges to adopting PLM is organizational change management given the breadth and scale of a true PLM solution . Many companies approaches it in phases and rightly so; but the key is how the phases are architected, tracked and measured. PLM involves managing and linking Data, Processes and People together as the product goes through it’s lifecycle from inception to design to manufacturing to support and eventually end of life. The first step of this is often managing Data; specifically Engineering CAD data. Most solutions start with a way to vault the CAD data along with some basic part numbering schemes and revision rules . Sometimes engineering documents are also vaulted along with the CAD data. Yes data vaulted in a central repository brings lot of benefits like elimination of duplicates , basic check-in-checkout / access controls and added search capabilities as opposed to it scattered across multiple locations. But the measured value of this alone may not substantiate the heavy PLM IT investment companies needs to make for a true scalable PLM platform. Sometimes there is an expectation misalignment on the full PLM value and just the data vaulting value . This at times sends companies to a long and lull “PLM assessment” period after data vaulting. Sometimes cultural resistance or organizational change overturns any momentum. Maybe a technical glitch or integration shortfall previously overlooked becomes a deal breaker . Over-scoped and under supported initiative can also run out of money or time.

Companies make a considerable amount of IT investment on the PLM platform upfront, so that they have a scalable solution for all phases and not just CAD vaulting. Most of the time they can add more capabilities and processes on the PLM platform without additional IT investments . So it’s very important to get past the initial data vaulting phase and move to the next phases to maximize the utilization of existing IT investments. Now the question is where do we go after CAD vaulting. This is where upfront PLM Roadmap definition is so important in terms of how the phases are architected, tracked and measured. For companies who have successfully completed data vaulting but do not have a formal PLM Roadmap defined yet, some of the next focus areas to consider can be Engineering process management, BOM Management, Change management , Requirements management , Project and Program management , in no specific order.

Share this:

Organizations invest huge sums of money in simulation software to avoid expensive and disruptive physical testing processes. But how long it really takes to make this transformation happen! One thing is sure; it does not happen in a day. The flow chart below explains the reason pictorially. The last two blocks “compare and improve model” and “compare and improve theory” make this transformation a longer process than expected.

Let’s explore the reasons behind it. Comparison is needed to make sure that simulation results mimic the physical testing results before latter can be discarded, partially or fully. The difference in results can be due to three main factors: lack of user competency, limitation of software used, lack of sufficient input data.

Lack of user competency: FEA analysts are not born in a day. The subject is complex to learn and so are the software associated with it. The ramp up time really depends on analyst background along with complexity of problem being simulated. Organizations usually make a choice between hiring expert and expensive analysts who can deliver the results right away or producing analysts of its own through class room and hands on trainings. First option saves time while the second saves money. CAE software development companies are also making big stories these days by introducing CAD embedded simulation tools that require nominal user competency. Nevertheless, the competency builds up over time.

Limitation of software used: Initial investment in simulation domain is usually small. It means two things: either number of users are less or software functionality is limited. With time, complexity of problems goes up but the software remains the same. A common example I have seen is of a customer starting with simple linear simulation workbench in CATIA and over period trying to simulate finite sliding contact problems with frictional interfaces in the same workbench. Users don’t realize that their problem complexity has exceeded the software capacity to handle and it’s time to upgrade. It’s always recommended that analysts get in touch with their software vendors whenever they anticipate an increase in simulation software capacity or functionality. A certified simulation software vendor is a trusted advisor who can really help.

Lack of sufficient input data: “Garbage in – Garbage out” is a very common phrase in simulation world. However, at times it is very difficult to get the right input for software in use. The complexity of input data can arise either from complex material behavior or from complex loading conditions. Example of complex material may be hyper-elasticity or visco-elasticity observed in elastomeric materials. Examples of complex loading may be real time multi block road load data to estimate fatigue life. Sometimes simple metallic structures exhibit complex behavior due to complex loading. Examples are high speed impact or creep loading. With time many material testing labs have come into existence that can perform in house testing to provide right input data for simulation.

Conclusion: You will come out of the vicious loop of physical and simulation results comparison after couple of iterations if you have three things in place: right people, right software product and right input data. If you need help in any of the three aspects, we are always available.

Share this:

Anyone who has dealt with Bill of Materials (BOM) knows about the challenges and complexities involved with it. Sometimes we get asked, managing a single BOM itself is cumbersome, then why do we even need another one in the form of a Manufacturing Bill of Material (mBOM)..?

What we have seen with our customers is that, when there is only one BOM then it is usually owned by the engineering department (CAD BOM/ eBOM) and will be available for the Manufacturing Department as a “read only”. This is not good enough for the manufacturing teams as they need to author and add data specific to manufacturing , for example manufacturing specific consumable parts like glue, oil or Tool Fixtures and such. Another key factor is how the BOM is structured; typically eBOM is structured around organization systems and functions and represent the product architecture, but for manufacturing team a mBOM needs to be organized according to the manufacturing assembly order.

When customers need to work towards the industry 4.0 goal, they need to have smarter manufacturing solutions and systems that provide more ways to capture the manufacturing business intelligence and then suggest solutions based on the previous patterns. With this in mind they need to invest in manufacturing BOM authoring and management area. During a mBOM adoption, the key is not to recreate the data that’s already in eBOM, but to reuse the eBOM and add additional information specific to manufacturing. That way there is both reuse and traceability of the data.

At a high level mBOM creation automation solutions exist in multiple flavors

Recipe based mBOM: In a recipe based mBOM, customers can initiate the mBOM creation via pre-configured templates pointing to eBOM. Based on the recipe stored with the template it will automatically fetch the engineering parts into mBOM. This kind of solution helps customers who have heavy standardization in their product offerings.

Reusable Manufacturing Assembly: In such a solution, customers can leverage the same manufacturing assembly across multiple product lines to reduce the design, development and procurement costs

New Offline Processing Solutions: This approach is to tailor the mBOM creation process and application to the customer need using customization. This standardizes and automates the process to capture the business intelligence and its reuse via customization.

Smarter Validations: Such solutions suggests what’s next to the business users, that way users spends less time discovering the problem and more time solving it.

Over all value of such solutions is not just the flexibility it offers the manufacturing team, it also reduces manufacturing process planning and execution lead time with improved structure accuracyand significant reduction in change reconciliation processing time.

Share this:

More often PLM starts as a CAD/Design data vault for many companies, later evolving to a design data exchange platform . Most successful companies are taking PLM beyond just a design data exchange and access control platform; to a knowledge driven decision support system. This means PLM not only needs to manage the multitude of information generated at various stages of the product lifecycle , but also capture the product development knowledge and feed it back to the product lifecyccle. For example, the requirements and design for a newer version of a product needs to be also driven by the knowledge elements captured from the previous version’s lefecycle, from inception to design to manufacturing and service.

When PLM stays just in the Design Engineering world, it’s constrained to exchange information and capture knowledge from downstream stages managed by disconnected, silo based systems. This results in engineers spending huge amount of time in data acquisition tasks. Industry studies shows that information workers spend 30-40% of their time only for information gathering and analysis, thus wasting time in searching for nonexistent information, failing to find existing information, validating the information or recreating information that can’t be found.

Quality escapes is another challenge with such disconnected systems when product doesn’t confirm with the engineering definition. Non-conformances found on the shop floor are costly to review and dispose and even more severe when the product is already on service. Reconciling change is also extremely challenging, especially its downstream propagation, resulting in significant productivity losses. Slow change processing along with quality escapes cause delays in new product introduction affecting the overall ability of the companies to compete.

The first step towards transforming PLM to a true knowledge driven decision support system is to extend it to the CAD/CAM/CNC process chain, thus taking it to the shopfloors. Such a solution helps to establish a continuous loop from Engineering into the shop floor for operations management and manufacturing execution systems (MES). Such a continuous loop system provide more ways to capture the business intelligence and then suggest solutions based on the previous patterns. Then it’s much easier to capture information and use analytics to synthesize valuable knowledge elements compared to the fragmented solutions many companies have today. It’s also a foundational element for establishing a Digital Twin per Industry 4.0 vision

Share this:

“What you buy makes a difference but from whom you buy makes a bigger difference”

Most often, I talk about greatness of our product offerings in my blog articles. Such kind of blogs assist prospective customers in choosing the right product. But the same product can be procured in multiple ways, either directly from the developer or through a value-added reseller also called as VAR. In this blog article, I would emphasize on how prospective customer should select the right VAR while purchasing a Dassault Systemes or Siemens simulation product.

The first thing a customer needs to verify is whether VAR is supplying just the product or the complete solution. The difference between the two is the “value added services” associated with product usage.

“Without value added services, it’s not possible for a reseller to become a value-added reseller.” Please identify if you are doing business with just a reseller or a value-added reseller. Remember, simulation tools are not easy to use. There is a learning curve associated with these tools that can greatly impact the ROI and break-even timeline. The productivity of the user can be substantially enhanced if he is associated with a reseller who can provide whole bunch of services to shorten the learning curve and achieve break-even faster. Now let’s look at what type of services makes a difference in simulation space.

We are talking about software sales as well as consulting, training and support. Our software partners, Dassault Systemes, Siemens and Autodesk offer a bunch of certifications around these four components to distinguish between just “resellers” and “value added resellers.” Being certified means reseller has enough resources and knowledge to execute a given task of sales or service. Let’s talk about each component with respect to Simulation:

Software: To sell any DS SIMULIA product, the associated VAR should have “SIMULIA V6 design sight” certification as a minimum. There are further brand certifications available such as Mid-Market Articulate for product highlight and Mid-Market Demonstrate for product technical demonstration. To sell FEMAP product from Siemens, the VAR must have “FEMAP technical certification” as a minimum. All these certifications are associated with timed examinations.

Training: Training should be an integral part of simulation software sales. It gives users enough knowledge to use the software product in production environment. To offer technical training on any SIMULIA product, the VAR should have “finite element analysis with Abaqus specialist” certification as a minimum.

Support: Once users are in production environment, technical support is required on continuous basis. While many answers related to product usage are in documentation, it’s not a full source of information. Many queries are model specific that require attention of a dedicated support engineer. To offer technical support on any SIMULIA product, the VAR should have at-least one engineer who has “SIMULIA technical support specialist” certification. This certification should be renewed every two years. It is associated with a lengthy and “hard to pass” support certification examination across all products of SIMULIA brand.

Consulting: Consulting service plays a big role when customer either does not have enough time or resources to execute projects in house in-spite of having software product. It happens during certain burst phases of demand. While there are no certification criteria for VAR’s related to consulting in simulation space, a dedicated consulting and delivery team is needed to offer the service when demand arises.

The above information should help you in ranking your VAR. Do you need to know our rank? Please contact us.

The second new feature is the ability to assign content of a structure to a project. While viewing structure content, users can assign the elements in the structure to projects. Users can multiply select elements, to assign them, or use the option to assign all of the content in a structure, or just to some level. Users can also assign the specifically referenced revisions, or to all revisions, so that as the structure content revises, it is also assigned to the project by default.

Assign projects to content while working within the context of a structure

Assign projects to entire structure or up to a specific level of the structure

Optionally apply project security to the revision or all revisions

Multi-select to assign projects

Effectivity Authoring

With Active Workspace 3.3, users can assign existing effectivity criteria to elements of the structure to indicate when those elements are applicable. Users can also define new effectivity criteria using dates or units. For example, this element is effective for this date range or for this range of production units.

Users can also name the effective ranges, to enable sharing, or reuse, of that same range when applying effectivity to other elements in the structure.

Optionally share named effectivity to apply to other content in structure or other structures

Baseline

Another complete the thought capability in the area of structures is creating a baseline. Baselines are used to capture a view of that structure at a point in time. Siemens chose to make this work in the background, asynchronously so that users can continue to work in the client as the server generates the baseline. When it completes, the Active Workspace notification center is used to alert users that the baseline has been created. By default, the process applies a release status of baseline, but that is configurable.

While the example shows a requirement structure, baselining works with any type of structure. Highlights include

Executes asynchronously to allow the user to continue other work

Notification sent on completion – click notification to open the baseline

Applies a release status of “Baseline” by default, but is configurable

Creates a precise baseline

Works with any structure content, e.g. parts, designs, and requirements

Show all Results from Find in Context

Lastly in the area of completing a thought is a visualization related topic. In previous releases of Active Workspace, the show only results in the viewer would only work for the results that had been loaded to the client. Users no longer have to scroll through all of the results to load them in the client before selecting the show only results in the viewer.

Share this:

One of the most exciting user productivity improvements in Active Workspace 3.3, is the new universal viewer. It enables viewing and paging through multiple file attachments. In prior releases, only one file could be viewed. You could not easily view other file attachments. Siemens also enabled support to view additional types of files including image files, text files, and html files. This viewer supports markup for many of those types as well.

This video showcases the new Universal Viewer capabilities in detail : Click here

Tab Overflow Direct Access

Previous versions of Active Workspace used a carousel approach and required multiple clicks to navigate to tabs that were hidden. The new approach allows for direct access to any of the hidden tabs. Highlights include

Siemens introduced command stacks in Active Workspace 3.2. This is an example of their usage in 3.3 to improve access to the 3D viewer’s analytics capabilities. Instead of having to navigate tabs, users can now directly access any of the features using the command stack. Highlights include

Administrators can configure alternative arrangements and visibility of commands for specific roles, e.g., commands can be unstacked or hidden for specific roles

This video shows how the command stack works for the viewer’s analytics capabilities: Click here

Drag and Drop in Structured Content

Active Workspace 3.2 supported cut/copy/paste to edit structures, including working across multiple browsers and across multiple structures. Active Workspace 3.3 builds on that capability to improve user productivity by enabling drag and drop for many cases as described below

Edit structures efficiently using drag and drop

Drag and drop between unstructured lists such as folders, search results, & favorites and structures

Drag within one window or across multiple windows

Drop action active only when dragged object is valid to be dropped on the target object

Predictable results based on context

Drag and drop between structures to copy content

Drag and drop content within a structure to move

Drag and drop different types of objects/elements to create relations – e.g. dropping a requirement on a part creates a tracelink